Genetic and Flower Volatile Diversity in Natural Populations of Origanum vulgare subsp. hirtum (Link) Ietsw. in Bulgaria: Toward the Development of a Core Collection - Alekseeva, Marina; Zagorcheva, Tzvetelina; Rusanova, Mila; Rusanov, Krasimir; Atanassov, Ivan (Frontiers in Plant Science, 2021)
We studied the genetic and flower volatile diversity in natural populations of Origanum vulgare subsp. hirtum (Link) Ietsw. in Bulgaria using simple sequence repeat (SSR) and sequence-related amplified polymorphism (SRAP) markers and gas chromatography/mass spectrometry (GC/MS) analysis of flower volatiles from individual plants. Two regions, including the Kresna Gorge and Eastern Rhodopes, typical for the species comprising eight populations and 239 individual plants were included in this study. An analysis with 11 SSR markers and eight SRAP primer combinations showed that SRAP markers were substantially more informative than the SSR markers and were further used for genetic diversity analysis. The results showed low-range to mid-range genetic differentiation between the populations with pairwise fixation index (Fst) values ranging between 0.0047 and 0.11. A total of 10 genetic clusters were identified. An analysis of the flower volatile diversity identified a total of 63 compounds with the vast majority of plants belonging to the carvacrol chemotype and just a single plant to the thymol chemotype. Large deviations were observed for individual compounds within each region as well as within the populations. Hierarchical clustering showed a clear sample grouping based on the two different regions. In addition, an in-depth analysis identified six major and 23 minor metabolite clusters. The overall data set and cluster analysis were further used for the development and testing of a simple and straightforward strategy for the selection of individual plants for the development of a core collection representing the sampled natural populations for this species in Bulgaria. The proposed strategy involves precise genetic clustering of the tested plants followed by the selection of a minimal set from each genetic cluster representing the different metabolite clusters. The selected core set was further compared with a core set extracted by the PowerCore software. A comparison of the genetic and metabolic affiliation of the members of both sets showed that the reported approach selected representatives from each genetic cluster and minor metabolic cluster, whereas some metabolic clusters were unrepresented in the PowerCore set. The feasibility and efficiency of applying the pointed strategy for the development of a core collection representing both the genetic and metabolite diversity of natural populations in aromatic and medicinal plants toward subsequent steps of selection and breeding are discussed.